Paper List

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Summary of Adapting Segment Anything Model to Melanoma Segmentation in Microscopy Slide Images, by Qingyuan Liu and Avideh Zakhor
Summary of Calibrate to Discriminate: Improve In-context Learning with Label-free Comparative Inference, by Wei Cheng et al.
Summary of Stochastic Sampling From Deterministic Flow Models, by Saurabh Singh et al.
Summary of Hyperbrain: Anomaly Detection For Temporal Hypergraph Brain Networks, by Sadaf Sadeghian et al.
Summary of Orient Anything, by Christopher Scarvelis et al.
Summary of Can Llms Reliably Simulate Human Learner Actions? a Simulation Authoring Framework For Open-ended Learning Environments, by Amogh Mannekote et al.
Summary of Ec-dit: Scaling Diffusion Transformers with Adaptive Expert-choice Routing, by Haotian Sun et al.
Summary of Mamba Neural Operator: Who Wins? Transformers Vs. State-space Models For Pdes, by Chun-wun Cheng et al.
Summary of Dataset Distillation Via Knowledge Distillation: Towards Efficient Self-supervised Pre-training Of Deep Networks, by Siddharth Joshi et al.
Summary of Searching For Efficient Linear Layers Over a Continuous Space Of Structured Matrices, by Andres Potapczynski et al.
Summary of Breaking the Mold: the Challenge Of Large Scale Marl Specialization, by Stefan Juang et al.
Summary of C-melt: Contrastive Enhanced Masked Auto-encoders For Ecg-language Pre-training, by Manh Pham et al.
Summary of Nonuniform Random Feature Models Using Derivative Information, by Konstantin Pieper and Zezhong Zhang and Guannan Zhang
Summary of Disentangled Representation Learning For Parametric Partial Differential Equations, by Ning Liu et al.
Summary of Trajgpt: Irregular Time-series Representation Learning For Health Trajectory Analysis, by Ziyang Song et al.
Summary of A Formal Framework For Understanding Length Generalization in Transformers, by Xinting Huang et al.
Summary of Plug-and-play Controllable Generation For Discrete Masked Models, by Wei Guo et al.
Summary of Active Learning Of Deep Neural Networks Via Gradient-free Cutting Planes, by Erica Zhang et al.
Summary of Efficient Source-free Time-series Adaptation Via Parameter Subspace Disentanglement, by Gaurav Patel et al.
Summary of Classcontrast: Bridging the Spatial and Contextual Gaps For Node Representations, by Md Joshem Uddin et al.
Summary of Quantitative Approximation For Neural Operators in Nonlinear Parabolic Equations, by Takashi Furuya et al.
Summary of Mitigating Memorization in Language Models, by Mansi Sakarvadia et al.
Summary of Adversarial Decoding: Generating Readable Documents For Adversarial Objectives, by Collin Zhang et al.
Summary of Adaptively Private Next-token Prediction Of Large Language Models, by James Flemings et al.
Summary of Review Non-convex Optimization Method For Machine Learning, by Greg B Fotopoulos et al.
Summary of Model Comparisons: Xnet Outperforms Kan, by Xin Li et al.
Summary of Deepprotein: Deep Learning Library and Benchmark For Protein Sequence Learning, by Jiaqing Xie et al.
Summary of Tuning Frequency Bias Of State Space Models, by Annan Yu et al.
Summary of Eab-fl: Exacerbating Algorithmic Bias Through Model Poisoning Attacks in Federated Learning, by Syed Irfan Ali Meerza et al.
Summary of Tpp-llm: Modeling Temporal Point Processes by Efficiently Fine-tuning Large Language Models, By Zefang Liu et al.
Summary of Realizable Continuous-space Shields For Safe Reinforcement Learning, by Kyungmin Kim et al.
Summary of Inspection and Control Of Self-generated-text Recognition Ability in Llama3-8b-instruct, by Christopher Ackerman and Nina Panickssery
Summary of Fast and Sample Efficient Multi-task Representation Learning in Stochastic Contextual Bandits, by Jiabin Lin et al.
Summary of Semi-supervised Fine-tuning Of Vision Foundation Models with Content-style Decomposition, by Mariia Drozdova et al.
Summary of Mmfnet: Multi-scale Frequency Masking Neural Network For Multivariate Time Series Forecasting, by Aitian Ma et al.
Summary of Posterior Sampling Via Langevin Dynamics Based on Generative Priors, by Vishal Purohit et al.
Summary of Kolmogorov-arnold Network Autoencoders, by Mohammadamin Moradi et al.
Summary of Deep Generative Modeling For Identification Of Noisy, Non-stationary Dynamical Systems, by Doris Voina and Steven Brunton and J. Nathan Kutz
Summary of Mixlinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1k Parameters, by Aitian Ma et al.
Summary of Emma: Efficient Visual Alignment in Multi-modal Llms, by Sara Ghazanfari et al.
Summary of Farm: Functional Group-aware Representations For Small Molecules, by Thao Nguyen et al.
Summary of Multi-omic and Quantum Machine Learning Integration For Lung Subtypes Classification, by Mandeep Kaur Saggi et al.
Summary of Anchors Aweigh! Sail For Optimal Unified Multi-modal Representations, by Minoh Jeong et al.
Summary of Social Media Authentication and Combating Deepfakes Using Semi-fragile Invisible Image Watermarking, by Aakash Varma Nadimpalli et al.
Summary of Is Uniform Expressivity Too Restrictive? Towards Efficient Expressivity Of Graph Neural Networks, by Sammy Khalife et al.
Summary of Provably Accurate Shapley Value Estimation Via Leverage Score Sampling, by Christopher Musco and R. Teal Witter
Summary of Ntk-dfl: Enhancing Decentralized Federated Learning in Heterogeneous Settings Via Neural Tangent Kernel, by Gabriel Thompson et al.
Summary of Step-by-step Reasoning For Math Problems Via Twisted Sequential Monte Carlo, by Shengyu Feng et al.
Summary of Marple: a Benchmark For Long-horizon Inference, by Emily Jin et al.
Summary of Llm-augmented Symbolic Reinforcement Learning with Landmark-based Task Decomposition, by Alireza Kheirandish et al.
Summary of Taegan: Generating Synthetic Tabular Data For Data Augmentation, by Jiayu Li et al.
Summary of Don’t Flatten, Tokenize! Unlocking the Key to Softmoe’s Efficacy in Deep Rl, by Ghada Sokar et al.
Summary of Chase-sql: Multi-path Reasoning and Preference Optimized Candidate Selection in Text-to-sql, by Mohammadreza Pourreza et al.
Summary of One-step Noisy Label Mitigation, by Hao Li et al.
Summary of Score-based Pullback Riemannian Geometry, by Willem Diepeveen et al.
Summary of Comadice: Offline Cooperative Multi-agent Reinforcement Learning with Stationary Distribution Shift Regularization, by the Viet Bui and Thanh Hong Nguyen and Tien Mai
Summary of Discrete Copula Diffusion, by Anji Liu et al.
Summary of Which Algorithms Have Tight Generalization Bounds?, by Michael Gastpar et al.
Summary of Scale-invariant Learning-to-rank, by Alessio Petrozziello et al.
Summary of Deep Learning Alternatives Of the Kolmogorov Superposition Theorem, by Leonardo Ferreira Guilhoto et al.
Summary of Normalizing Flow-based Metric For Image Generation, by Pranav Jeevan et al.
Summary of Fairlyuncertain: a Comprehensive Benchmark Of Uncertainty in Algorithmic Fairness, by Lucas Rosenblatt and R. Teal Witter
Summary of Addressing Data Heterogeneity in Federated Learning with Adaptive Normalization-free Feature Recalibration, by Vasilis Siomos et al.
Summary of Bayesian Binary Search, by Vikash Singh et al.
Summary of Toper: Topological Embeddings in Graph Representation Learning, by Astrit Tola et al.
Summary of Composing Global Optimizers to Reasoning Tasks Via Algebraic Objects in Neural Nets, by Yuandong Tian
Summary of Open-rag: Enhanced Retrieval-augmented Reasoning with Open-source Large Language Models, by Shayekh Bin Islam et al.
Summary of Investigating on Rlhf Methodology, by Alexey Kutalev and Sergei Markoff
Summary of Learning to Solve Differential Equation Constrained Optimization Problems, by Vincenzo Di Vito et al.
Summary of Knowledge-driven Feature Selection and Engineering For Genotype Data with Large Language Models, by Joseph Lee et al.
Summary of Bellman Diffusion: Generative Modeling As Learning a Linear Operator in the Distribution Space, by Yangming Li et al.
Summary of Proxi: Challenging the Gnns For Link Prediction, by Astrit Tola et al.
Summary of Analysis Of Convolutional Neural Network-based Image Classifications: a Multi-featured Application For Rice Leaf Disease Prediction and Recommendations For Farmers, by Biplov Paneru et al.
Summary of On the Expressiveness and Spectral Bias Of Kans, by Yixuan Wang et al.
Summary of Bayes-catsi: a Variational Bayesian Deep Learning Framework For Medical Time Series Data Imputation, by Omkar Kulkarni and Rohitash Chandra
Summary of Spatial Action Unit Cues For Interpretable Deep Facial Expression Recognition, by Soufiane Belharbi et al.
Summary of An Early-stage Workflow Proposal For the Generation Of Safe and Dependable Ai Classifiers, by Hans Dermot Doran et al.
Summary of Explainable Diagnosis Prediction Through Neuro-symbolic Integration, by Qiuhao Lu et al.
Summary of House Of Cards: Massive Weights in Llms, by Jaehoon Oh et al.
Summary of Frednormer: Frequency Domain Normalization For Non-stationary Time Series Forecasting, by Xihao Piao et al.
Summary of Learning the Optimal Path and Dnn Partition For Collaborative Edge Inference, by Yin Huang et al.
Summary of Neat: Nonlinear Parameter-efficient Adaptation Of Pre-trained Models, by Yibo Zhong et al.
Summary of Conformal Prediction Sets Can Cause Disparate Impact, by Jesse C. Cresswell et al.
Summary of Vineppo: Unlocking Rl Potential For Llm Reasoning Through Refined Credit Assignment, by Amirhossein Kazemnejad et al.
Summary of Phi-s: Distribution Balancing For Label-free Multi-teacher Distillation, by Mike Ranzinger et al.
Summary of Positional Attention: Expressivity and Learnability Of Algorithmic Computation, by Artur Back De Luca et al.
Summary of Uncertainty Quantification with Bayesian Higher Order Relu Kans, by James Giroux et al.
Summary of Morel: Enhancing Adversarial Robustness Through Multi-objective Representation Learning, by Sedjro Salomon Hotegni et al.
Summary of Sable: a Performant, Efficient and Scalable Sequence Model For Marl, by Omayma Mahjoub et al.
Summary of Meta-ttt: a Meta-learning Minimax Framework For Test-time Training, by Chen Tao et al.
Summary of Towards a Theoretical Understanding Of Synthetic Data in Llm Post-training: a Reverse-bottleneck Perspective, by Zeyu Gan et al.
Summary of Automated Knowledge Concept Annotation and Question Representation Learning For Knowledge Tracing, by Yilmazcan Ozyurt et al.
Summary of Evaluating Robustness Of Reward Models For Mathematical Reasoning, by Sunghwan Kim et al.
Summary of Laser: Learning to Adaptively Select Reward Models with Multi-armed Bandits, by Duy Nguyen et al.
Summary of Recursive Abstractive Processing For Retrieval in Dynamic Datasets, by Charbel Chucri et al.
Summary of Mimicking Human Intuition: Cognitive Belief-driven Q-learning, by Xingrui Gu et al.
Summary of Prend: Enhancing Intrinsic Motivation in Reinforcement Learning Through Pre-trained Network Distillation, by Mohammadamin Davoodabadi et al.
Summary of Leray-schauder Mappings For Operator Learning, by Emanuele Zappala
Summary of Not All Llm Reasoners Are Created Equal, by Arian Hosseini et al.
Summary of Torchsisso: a Pytorch-based Implementation Of the Sure Independence Screening and Sparsifying Operator For Efficient and Interpretable Model Discovery, by Madhav Muthyala and Farshud Sorourifar and Joel A. Paulson